Atmos. Chem. Phys., 16, 13389–13398, 2016
www.atmos-chem-phys.net/16/13389/2016/
doi:10.5194/acp-16-13389-2016
© Author(s) 2016. CC Attribution 3.0 License.
Composition and oxidation state of sulfur in
atmospheric particulate matter
Amelia F. Longo1 , David J. Vine2 , Laura E. King1 , Michelle Oakes3 , Rodney J. Weber1 , Lewis Gregory Huey1 ,
Armistead G. Russell1 , and Ellery D. Ingall1
1 School
of Earth and Atmospheric Sciences, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, GA 30332, USA
Photon Source, Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439, USA
3 Tennessee Department of Environment and Conservation, Division of Air Pollution Control, Nashville, TN 37206, USA
2 Advanced
Correspondence to: Ellery D. Ingall ([email protected])
Received: 19 May 2016 – Published in Atmos. Chem. Phys. Discuss.: 27 May 2016
Revised: 26 July 2016 – Accepted: 2 October 2016 – Published: 31 October 2016
Abstract. The chemical and physical speciation of atmospheric sulfur was investigated in ambient aerosol samples
using a combination of sulfur near-edge x-ray fluorescence
spectroscopy (S-NEXFS) and X-ray fluorescence (XRF) microscopy. These techniques were used to determine the composition and oxidation state of sulfur in common primary
emission sources and ambient particulate matter collected
from the greater Atlanta area. Ambient particulate matter
samples contained two oxidation states: S0 and S+VI . Ninetyfive percent of the individual aerosol particles (> 1 µm) analyzed contain S0 . Linear combination fitting revealed that
S+VI in ambient aerosol was dominated by ammonium sulfate as well as metal sulfates. The finding of metal sulfates provides further evidence for acidic reactions that solubilize metals, such as iron, during atmospheric transport.
Emission sources, including biomass burning, coal fly ash,
gasoline, diesel, volcanic ash, and aerosolized Atlanta soil,
and the commercially available bacterium Bacillus subtilis,
contained only S+VI . A commercially available Azotobacter vinelandii sample contained approximately equal proportions of S0 and S+VI . S0 in individual aerosol particles
most likely originates from primary emission sources, such
as aerosolized bacteria or incomplete combustion.
1
Introduction
Sulfur (S) in atmospheric aerosols has garnered significant
interest because of its influence on environmental processes
(Bufalini, 1971; Galloway, 1995; Van Grieken et al., 1998)
and human health (Burnett et al., 1995). Sulfur-rich aerosol
can serve as cloud condensation nuclei. On a global scale,
cloud condensation nuclei participate in cloud formation
processes to change atmospheric albedo (Charlson et al.,
1987; Quinn and Bates, 2011), which can ultimately influence global climate. Atmospheric sulfur is responsible for
the production of sulfuric acid, which has been implicated
in the solubilization of metals in aerosol (Wiederhold et al.,
2006; Nenes et al., 2011; Sullivan et al., 2007; Oakes et al.,
2012a). Solubilization of recalcitrant mineral phases during
atmospheric transport can release nutrient elements, such as
iron, which impacts biological productivity in many oceanic
regions (Longo et al., 2014, 2016; Mahowald et al., 2005;
Jickells et al., 2005). Additionally, soluble metals present in
the urban environment may cause adverse respiratory events
among affected populations (Fang et al., 2016; Pardo et al.,
2016).
The range of sulfur oxidation states as well as organic and
inorganic forms present in typical samples confounds characterization of aerosol sulfur. Characterization approaches,
including ion chromatography, X-ray fluorescence, and inductively coupled plasma mass spectrometry, have been used
to quantify bulk elemental or bulk concentrations, which can
be used to infer the composition of sulfur in aerosols. However, these techniques cannot determine the oxidation state or
directly identify the chemical form of aerosol sulfur. Several
studies have demonstrated the effectiveness of synchrotronbased sulfur X-ray absorption near-edge structure (XANES)
and the closely related sulfur near-edge X-ray fluorescence
spectroscopy (NEXFS) to determine the oxidation state and
Published by Copernicus Publications on behalf of the European Geosciences Union.
13390
chemical form of sulfur in environmental samples (Solomon
et al., 2003; Prietzel et al., 2011; Morra et al., 1997; Farges
et al., 2009); however, the application of these techniques
to ambient aerosol samples has largely been limited to studies characterizing a few ambient aerosol samples that aim to
explore the feasibility and limits of applying XANES and
NEXFS to aerosol sulfur studies (Takahashi et al., 2006;
Pongpiachan et al., 2012a, b; Higashi and Takahashi, 2009;
Cozzi et al., 2009).
Consistent with traditional techniques, synchrotron-based
XANES studies indicate that sulfur occurs primarily in the
S+VI oxidation state, largely as inorganic sulfate compounds.
Primary emission sources of S+VI include both anthropogenic and biogenic sources, including combustion of fossil
fuels, biomass burning, volcanoes, and sea spray (Querol et
al., 2000). Sulfur in aerosol, ranging in oxidation state from
S−II to S+IV , has also been identified in smaller quantities
through the use of XANES techniques (Huggins et al., 2000;
Eatough et al., 1978; Cao et al., 2015; Higashi and Takahashi,
2009; Craig et al., 1974; Cozzi et al., 2009). Primary sources
of reduced sulfur to the atmosphere are mainly attributed to
gaseous emissions from volcanic gases, hot springs, bacteria,
vehicle exhaust, and oil refineries (Cozzi et al., 2009; Andersson et al., 2006). While detected in the solid phase, reduced
sulfur in aerosols has not been extensively studied. Reduced
aerosol sulfur may reflect a contribution from primary emission sources or may result from condensation of volatile reduced sulfur gaseous phases, but the ultimate origin of reduced sulfur in aerosol particulates remains unresolved.
Here we use S-NEXFS to investigate the composition and
oxidation state of sulfur in ambient aerosols and common
primary emission source samples. Previous S-NEXFS studies characterized a limited number of ambient aerosol samples in bulk, providing an average view of the sulfur oxidation state and composition in particulate matter (Higashi
and Takahashi, 2009; Takahashi et al., 2006; Pongpiachan et
al., 2012a, b; Long et al., 2014). Recent studies of aerosol
iron and selenium have demonstrated that analyzing compositional differences between large particles (> 1 µm) and the
bulk sample can help elucidate aerosol sources and transformations (Longo et al., 2016; Oakes et al., 2012b; De Santiago
et al., 2014). Following a similar approach, we used a combination of bulk and individual particle S-NEXFS analyses
to characterize aerosol sulfur in rural and urban samples and
from different emission sources. The spatial distribution of
sulfur oxidation states was also characterized in individual
particles by mapping particles at different incident energies
to gain further insights into the processes surrounding the
formation of reduced sulfur species in aerosol.
Atmos. Chem. Phys., 16, 13389–13398, 2016
A. F. Longo et al.: Composition and oxidation state of sulfur
2
2.1
Methods
Ambient aerosol collection
PM2.5 samples were collected from urban and rural locations in and around Atlanta, GA, USA. The five sampling sites, South DeKalb, Fire Station 8, Jefferson Street,
Yorkville, and Fort Yargo State Park, are associated with
two ongoing studies, the Southeastern Aerosol Research and
Characterization (SEARCH) study (Edgerton et al., 2005,
2006; Hansen et al., 2003) and the Assessment of Spatial
Aerosol and Composition in Atlanta (Butler et al., 2003).
Samples were collected on Zefluor filters over 24 h periods at a flow rate of 16.7 L min−1 using cyclone inlet
samplers (URG, Chapel Hill, NC, USA). The multichannel particle samplers were mounted approximately 2.5 m off
the ground. Three samples were collected from Yorkville
(33◦ 550 42.3 N, 85◦ 20 43.68 W), a rural background site for
the Atlanta area. Two samples were collected from Jefferson Street (33◦ 460 38.94 N, 84◦ 240 59.58 W), an urban collection site that is not immediately influenced by any individual
source or roadside traffic. Five samples were collected from
Fort Yargo State Park (33◦ 580 4.18 N, 83◦ 430 29.16 W), a rural setting that is frequently impacted by biomass burning
plumes and power plant emissions. Four samples were collected in South DeKalb, a mixed commercial–residential area
approximately 1 km from a major interstate (33◦ 410 16.48 N,
84◦ 170 25.26 W). Seven samples were collected from Fire
Station 8, located in an industrial area in close proximity
to a rail yard, a fire station, and an intersection with heavy
diesel truck traffic (33◦ 480 6.01 N, 84◦ 260 8.75 W; Table S1 in
the Supplement).
2.2
Emission source collection
PM2.5 samples were collected from gasoline and diesel exhaust, biomass burning, and coal fly ash (Oakes et al.,
2012a). Emissions from ultra-low sulfur diesel fuel running a
10.8 L engine and conventional gasoline fuel running a 3.3 L
engine were collected according to US Environmental Protection Agency protocols under typical urban driving conditions (Liu et al., 2008; Oakes et al., 2012a). Polydisperse
coal fly ash, provided by Southern Company, from an electrostatic precipitator of a midsized coal-fired power plant was
aerosolized and collected with a cyclone inlet sampler to separate the PM2.5 fraction (Oakes et al., 2012a). Smoke produced from the burning of materials collected from coniferous and deciduous trees native to Georgia, USA, was sampled during a controlled biomass burning experiment using a
cyclone inlet sampler placed 3.5 m above the burn area at a
flow rate of 16.7 L min−1 for approximately 30 min. The ash
produced from the biomass burning experiment was analyzed
in the same manner. The abovementioned primary emission
source samples were collected on polytetrafluoroethylene
(Zefluor) filters (Longo et al., 2014). In addition, two comwww.atmos-chem-phys.net/16/13389/2016/
A. F. Longo et al.: Composition and oxidation state of sulfur
mercially available bacteria samples, Azotobacter vinelandii
(Sigma A2135) and Bacillus subtilis (Sigma B4006), were
homogenized with agate mortar and pestle and mounted on a
cellulose acetate filter for analysis.
All samples were immediately stored after preparation
in clean Petri dishes at −20 ◦ C until analysis. Preparation
for synchrotron analyses consisted of mounting an approximate 0.5 cm × 0.5 cm section of ambient aerosol and primary
emission source filters over a slot on an aluminum support.
2.3
Sulfate standards
In order to create a database of inorganic sulfate standards
necessary for the data analysis described below, 10 compounds were analyzed using the same experimental setup and
synchrotron system as the ambient aerosols. These standards
included ammonium sulfate (CAS 7783-20-2), barite, copper(II) sulfate (CAS 7758-98-7), gypsum, iron ammonium
sulfate (CAS 7783-85-9), iron(III) sulfate (CAS 15244-107), jarosite (KFe3+
3 (OH)6 (SO4 )2 , magnesium sulfate (CAS
7487-88-9), potassium sulfate (CAS 7778-80-5), and sodium
sulfate (CAS 7757-82-6). The sulfur standards were ground
using an agate mortar and pestle to the consistency of a
fine talcum powder (approximately 10 µm). A cellulose acetate filter was then gently dredged through a small quantity (less than 1 mg) of powder placed on a microscope slide.
This procedure produced a thin and almost imperceptible
coating on the filter in order to limit the thickness and thus
self-absorption. S-NEXFS spectra of sulfate standards were
collected in bulk mode. Self-absorption must be carefully
controlled when measuring fluorescent X-rays from thick
specimens; however, the effects of self-absorption are limited to the region of the spectrum above the K-edge (Bajt
et al., 1993; Iida and Noma, 1993). In our repeated measurements, the post-edge features were consistent and reproducible, which allows us to distinguish between sulfate standards. A database of sulfate standards is provided in the Supplement.
2.4
Synchrotron-based spectromicroscopy
Samples were analyzed on the X-ray fluorescence microscope located at beamline 2-ID-B at the Advanced Photon
Source, Argonne National Laboratory. The beamline is optimized to examine samples over a 1–4 keV energy range using a focused X-ray beam with a spot size of approximately
60 nm2 (McNulty et al., 2003). The energy was calibrated
using an elemental sulfur standard (S0 ). The whiteline energy of the elemental sulfur standard was aligned to 2472 eV
(Cozzi et al., 2009). Sulfur near-edge X-ray fluorescence
spectroscopy (S-NEXFS) data were collected in two modes
that differ based on spatial resolution. In the first mode, individual sulfur-rich particles with a diameter greater than 1 µm
were identified in X-ray fluorescence maps; these particles
were then interrogated with micro-S-NEXFS. The number
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of individual particles examined that provided usable spectra
are provided in Table S1. The individual sulfur-rich particles
seen in X-ray fluorescence maps are obvious contributors to
the total sample sulfur. However, much of the total sulfur on
an aerosol filter can also be contained in particles that are
smaller than 1 µm or less sulfur-rich and therefore less apparent in X-ray fluorescence maps. Consequently, in the second
mode, large areas of the filters were also examined with an
unfocused beam (spot size = 0.25 mm).
In order to maximize the number of samples analyzed in
the allotted time, X-ray fluorescence (XRF) maps were created for a subset of samples by rastering the sample through
the focused beam in 0.5 µm steps with an incident energy
of 2535 eV. At this resolution, individual sulfur-rich particles
were clearly discernible. S-NEXFS spectra were scanned
over a 50 eV range centered at 2485 eV in 0.33 eV steps, using a 1 s dwell time at each step. Here, dwell time is used
to refer to the time spent at each step in the S-NEXFS spectrum or each pixel in an XRF map. Each S-NEXFS measurement for both bulk and individual sulfur-rich particles were
repeated at least three times in a single location, creating a
minimum effective dwell time of 3 s. For these settings, the
total scan time would be approximately 7.5 min. X-ray spectromicroscopy data were collected using an energy dispersive
silicon drift detector (Vortex with a 50 mm2 sensitive area).
A flow of helium was introduced between the X-ray optical
hardware and the sample to reduce elastically scattered Xray background. An in-line monitor stick coated with an aluminum sulfate standard was measured in parallel with each
sample in order to identify and correct for any potential drift
in monochromator energy calibration that can occur during
analyses (de Jonge et al., 2010), meaning that for every spectral measurement two spectra are collected: the specimen and
an aluminum sulfate standard on the monitor stick. Because
the energy was calibrated using elemental sulfur S0 , all the
data use 2472 eV as the reference energy for S0 during the
data alignment to the monitor stick. Oxidation tests were also
done on a few samples where the same region or particle was
measured repeatedly, creating effective dwell times of more
than 10 s. Even with this longer dwell time, there was no noticeable shift in oxidation state or the relative abundance of
the oxidation states in the tested samples. Clean areas of filter
were examined as blanks and showed negligible background
signal.
S-NEXFS provides essentially the same information as
another commonly cited technique, S-XANES (sulfur Xray absorption near-edge structure) spectroscopy. The two
techniques differ primarily in the method of signal detection. S-NEXFS uses the X-ray fluorescence signal, which
is inversely proportional to the absorption signal used in a
XANES measurement.
Additionally, XRF microscopy was conducted in two
modes. First, to map the distribution of sulfur regardless
of oxidation state, an incident energy above the S K-edge
(2535 eV) was used, and samples were rastered through the
Atmos. Chem. Phys., 16, 13389–13398, 2016
focused beam in 0.5 µm steps, as mentioned above. In the
second mode, the spatial distribution of S0 and S+VI oxidation states were quickly mapped by selecting an incident Xray energy tuned to their specific whiteline energies. Because
of the energy drift at this beamline, it is important to identify
the correct whiteline energies for the multi-energy mapping;
therefore, a S-NEXFS spectrum was collected for the particle
of interest immediately before mapping. The corresponding
whiteline energies for S0 and S+VI were then taken directly
off this spectrum. Individual maps were then collected at the
whiteline energies determined for S0 and S+VI . Although it is
possible that the energy drifted during mapping, the interval
between the two measurements is short enough that this is not
a problem. Due to the 6 eV difference between the whiteline
energies of S0 and S+VI , we do not expect significant overlap
between the two oxidation states in multi-energy mapping.
Energy drift during mapping may reduce signal intensities of
S0 and S+VI , but the overall distribution patterns of the sulfur oxidation states in the individual particle should remain
relatively unaffected. These multi-energy XRF maps were
completed in 0.3 µm spatial resolution and 0.5 s dwell time
per pixel. X-ray focusing was adjusted to maintain a consistent beam spot size at both energies; however, some shift in
the final image did occur. The images were aligned using the
stack registration function of the Fiji software (Schindelin et
al., 2012).
A. F. Longo et al.: Composition and oxidation state of sulfur
Relative abundance
13392
S+VI
0.5
0.0
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Emission source
Figure 1. Oxidation state of sulfur in common emission sources.
Common emission sources were generally dominated by S+VI
(grey). Only the bacteria sample Azotobacter vinelandii showed a
signal for S0 as well as S+VI .
computes an error term, R factor, to quantify the goodness
of fit produced by a particular linear combination of standard
S-NEXFS spectra. The linear combination of standards that
yielded the lowest R factor reflects the best fit (Ravel and
Newville, 2005).
3
2.5
S0
1.0
Results
Data analysis
3.1
S-NEXFS data were normalized to create a relative intensity
value of approximately 1 for post-edge area of the spectra.
The data were also processed using a three-point smoothing
algorithm built into the software package Athena to remove
high-frequency noise (Ravel and Newville, 2005). The relative contribution of each oxidation state can be determined
by assuming the entire area under the whiteline peaks is representative of total sulfur, and the area under each whiteline peak represents the relative contribution of each oxidation state (Huffman et al., 1991; Xia et al., 1998). The area
under the whiteline peaks was determined using the Gaussian peak fitting function of Athena (Ravel and Newville,
2005) (Fig. S1 in the Supplement). Because of the relatively
low contribution of other sulfur oxidation states, only sulfur
species containing S+VI oxidation state could be further characterized via linear combination fitting. Linear combination
fitting is an effective tool for the deconvolution of spectra
of known mixtures (Longo et al., 2014; Long et al., 2014;
Huffman et al., 1991; Solomon et al., 2003; Prietzel et al.,
2011). Using Athena software, individual particle and bulk SNEXFS spectra were fit with previously characterized sulfate
standard materials using a linear combination approach to
determine both speciation and relative abundance of sulfate
phases (Ravel and Newville, 2005) (Fig. S2). Athena uses a
nonlinear, least-squares minimization approach to fit spectra
of unknown materials with spectra of standard materials and
Atmos. Chem. Phys., 16, 13389–13398, 2016
Oxidation state
Azotobacter vinelandii, Bacillus subtilis, gasoline and diesel
exhaust, biomass burning, and coal fly ash were only characterized at the bulk level (approximately 0.28 mm2 filter area).
These common primary emission sources, with the exception
of one bacteria sample, contained sulfur solely in the S+VI
oxidation state. Azotobacter vinelandii was the only emission source to contain both oxidized and reduced sulfur, with
approximately 44 % S+VI and 56 % S0 (Fig. 1).
At the bulk level, the oxidation state of sulfur in ambient
PM2.5 samples is dominated by S+VI ; only two samples from
South DeKalb contain S0 at quantities of less than 10 % total sulfur (Fig. 2). In contrast, individual particles with aerodynamic diameters of greater than 1 µm consistently contain
both S+VI and S0 (Fig. 3). Only 1 out of 23 individual particles analyzed did not contain S0 . At Fire Station 8 and Jefferson Street, the individual particles sampled contain on average 10 % S0 . Individual particles from South DeKalb average only 4 % S0 . The rural individual particles sampled from
Fort Yargo and Yorkville contain on average 5 and 9 % S0 , respectively. Multi-energy maps revealed that S+VI was present
throughout the aerosol particle. Often the highest concentration of S+VI was in the center of the particle, where the most
mass is present (Fig. S3). The spatial distribution of S0 was
more varied. In some cases, the S0 was concentrated in the
center of the particle with a less prominent ring on the outside
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Relative abundance
A. F. Longo et al.: Composition and oxidation state of sulfur
13393
1.0
0.5
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Sampling date
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Relative abundance
Figure 2. Bulk oxidation state of ambient particulate matter samples. Ambient particulate matter samples were characterized at the bulk
level for oxidation state. Here, the fractional relative abundance of S0 (black) and S+VI (grey) are shown for each of the ambient particulate
matter samples. S0 is only present in two samples collected from South DeKalb. The remaining samples contain only S+VI when examined
in bulk.
1.0
0.5
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8 11 11 11 11 11 lb 11 11 11 11 treet12 12 go 11 11 11 11 11 08 08 08 08 08 lle 12 12
ion 11. 11. 11. 11. 11. Ka 24. 24. 24. 24. S 24. 24. ar 10. 10. 10. 10. 10. 17. 17. 17. 17. 17. kvi 20. 20.
tat 8. 8. 8. 8. 8. h De 8. 8. 8. 8. rson 5. 5. ort Y 6. 6. 6. 6. 6. 9. 9. 9. 9. 9. Yor 6. 6.
S
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Sampling date
S0
S+VI
Figure 3. Oxidation state of individual aerosol particles. The oxidation state of sulfur was examined in individual particles from a subset
of samples. The fractional relative abundance of S0 (black) and S+VI (grey) is shown for each particle interrogated with S-NEXFS. At the
individual particle level, sulfur is consistently seen at both the S0 and S+VI oxidation states.
of the particle. In other cases, the S0 was most concentrated
in only one area of the particle (Fig. S3).
3.2
Sulfate composition
The relative contribution of different sulfur species can be
determined by the deconvolution of S-NEXFS spectra with
linear combination fitting (Prietzel et al., 2011; Ravel and
Newville, 2005). In these samples, only S+VI could be further characterized through linear combination fitting because
it was by far the most abundant species of sulfur present
in the samples. The regions of the S-NEXFS spectra represented by the lower sulfur oxidation states did not possess
sufficient detail to yield compositional information. Because
of spectral similarities between various metal sulfates, linear
combination fits using copper(II) sulfate or iron(III) sulfate
often yielded fits with similar R factors. This makes the absolute determination of metal sulfate composition difficult;
thus, iron(III) sulfate, copper(II) sulfate, and jarosite are referred to collectively as metal sulfates. The specific compositional information derived from the best linear combinawww.atmos-chem-phys.net/16/13389/2016/
tion fits, i.e., iron(III) sulfate, copper(II) sulfate, or jarosite,
is presented in Tables S2 and S3, and suggests that a combination of iron and copper sulfates is likely present in these
samples. In common primary emission sources and ambient PM2.5 , S+VI corresponded to sulfate aerosol. In emission sources, only biomass burning, coal fly ash, and diesel
exhaust had robust enough signals to characterize specific
sulfate composition, and each source had a unique sulfate
composition (Table S3). Biomass burning contained potassium sulfate (100 ± 0.005 %). Coal fly ash contained gypsum (100 ± 0 %), the mineral form of calcium sulfate. Diesel
exhaust contained ammonium sulfate (70 ± 11 %) and metal
sulfate (30 ± 12 %).
The composition of sulfate was generally consistent within
a sampling location (Table S3 and Fig. 4). At the bulk
level, rural sampling locations contain a mix of ammonium
sulfate and metal sulfate. Yorkville samples are comprised
of 61 ± 9 % ammonium sulfate and 39 ± 9 % metal sulfate,
and Fort Yargo samples contain 84 ± 7 % ammonium sulfate and 16 ± 7 % metal sulfate. Bulk urban samples all contain a large fraction of ammonium sulfate. Samples from
Atmos. Chem. Phys., 16, 13389–13398, 2016
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A. F. Longo et al.: Composition and oxidation state of sulfur
potassium sulfate with additional contributions from metal
sulfate and gypsum. Spectral signals of samples from Jefferson Street and Yorkville were not strong enough to characterize the composition of sulfate in the ambient PM2.5 samples.
Relative abundance
100 %
75 %
50 %
25 %
4
0%
Ammonium sulfate
Gypsum
Metal sulfates
Potassium sulfate
Relative abundance
100 %
75 %
50 %
25 %
0%
Ammonium sulfate
Gypsum
Potassium sulfate
Metal sulfates
Figure 4. Composition of aerosol sulfate. Bulk (top) and individual
particle (bottom) composition of sulfur in ambient particulate matter. For bulk samples, the composition of sulfate was consistent for
all samples within a particular sampling location, with the exception
of South DeKalb. These samples had three different compositional
groups, and the month and year of collection are provided next to
the samples. For individual particles, the sulfate composition was
able to be determined for samples from Fire Station 8 (FS8), Fort
Yargo (FY), and South DeKalb (SD). Different particles from the
same samples are numbered sequentially (P1–P5).
Fire Station 8 contain ammonium sulfate (84 ± 7 %) mixed
with metal sulfate (14 ± 16 %), and Jefferson Street contains
ammonium sulfate (51 ± 8 %) combined with metal sulfate
(50 ± 10 %). South DeKalb has three different compositional
groups at bulk level: (1) ammonium sulfate (63 ± 7 %), metal
sulfate (29 ± 6 %), and potassium sulfate (8 ± 13 %); (2) ammonium sulfate (42 ± 14 %) and metal sulfate (58 ± 14 %);
and (3) gypsum (43 ± 15 %) and metal sulfate (58 ± 15 %).
Only individual particle S-NEXFS spectra from Fire Station 8, Fort Yargo, and South DeKalb contained enough
sulfur to determine the sulfate composition (Table S3 and
Fig. 4). In total, 17 individual particle S-NEXFS spectra were
used to gain insights on the sulfate composition of ambient
PM2.5 . Consistent with the bulk results, individual particles
sampled from Fire Station 8 are largely ammonium sulfate
and metal sulfate, with the remainder made of gypsum. Individual particles from South DeKalb contain either ammonium sulfate or metal sulfate. Individual particles from Fort
Yargo contain a mixture of mostly ammonium sulfate and
Atmos. Chem. Phys., 16, 13389–13398, 2016
Discussion
Ammonium sulfate and gypsum are commonly identified
phases in studies of aerosol sulfate composition (Long et al.,
2014; Higashi and Takahashi, 2009; Takahashi et al., 2006).
Consistent with these studies, ammonium sulfate was found
across all urban and rural sampling locations, and either ammonium sulfate or gypsum was a major constituent of all
bulk samples. At the individual particle level, ammonium
sulfate was also a primary contributor to sulfate composition;
however, potassium and metal sulfates became more apparent. Our results showed that the sulfate in biomass burning
was dominated by potassium sulfate, which suggests biomass
burning may be the primary source of the potassium sulfate in ambient aerosol samples. Potassium is often used as
a tracer for biomass burning in source apportionment studies (Viana et al., 2008), which show that biomass burning
can contribute up to 40 % of total PM2.5 in Georgia’s spring
months and 10 % of total PM2.5 in Georgia’s summer months
(Tian et al., 2009). Organosulfates have recently been identified as a significant component of sulfate aerosol (Liao et
al., 2015; Schmitt-Kopplin et al., 2010; Surratt et al., 2008;
Xu et al., 2015). In this study, organosulfates were not identified as a constituent of sulfate aerosol. While organosulfates are not present in our sulfate standard database, we were
able to account for all the sulfate in our samples without this
class of compounds. However, the expected concentration of
organosulfates in ambient aerosol could be near or below
10 %, which is the detection limit of linear combination fitting techniques (Longo et al., 2014; Oakes et al., 2012a, b).
Therefore, organosulfates may still be present in small quantities.
Metal sulfates were identified as a constituent of all the
bulk ambient particulate matter samples and 53 % of individual particle spectra. Linear combination fitting of SNEXFS spectra suggests that iron(III) sulfates are an important group of metal sulfates in ambient Atlanta aerosol
(Table S2 and S3). Furthermore, an Fe-XANES study of ambient Atlanta particulate matter identified iron(III) sulfates,
which accounted for approximately 20 % of the total iron
(Oakes et al., 2012a). Iron sulfate represents a very soluble, bioavailable form of iron that has been found in ambient aerosol (Zhang et al., 2014; Moffet et al., 2012; Schroth
et al., 2009; Oakes et al., 2012a). Diesel exhaust was the
only primary emission source to contain metal sulfates in this
study, and because source apportionment studies show that
diesel emissions account for approximately 5.3 % of PM2.5
in Atlanta (Hu et al., 2014), it is unlikely that diesel exhaust
alone can explain the quantities of metal sulfates found in
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A. F. Longo et al.: Composition and oxidation state of sulfur
our ambient aerosol samples. This could suggest that secondary processes play a role in the composition of S+VI in
ambient aerosol samples. Iron sulfate may be the end product of acidic reactions hypothesized to occur in the atmosphere that are responsible for solubilizing iron. Correlations
between the sulfur content and iron solubility have previously been used to suggest that this mechanism plays a role
in shaping the composition of iron in ambient Atlanta aerosol
(Oakes et al., 2012a). Briefly, sulfuric acid solubilizes more
crystalline iron phases, resulting in a solution rich in soluble
iron and sulfate that can become internally mixed and potentially precipitate out as iron(III) sulfate (Moffet et al., 2012;
Zhang et al., 2014; Oakes et al., 2012a). Evidence of similar processes has been found for copper (Fang et al., 2015),
which is another metal that is likely present in these samples
(Tables S2 and S3). The metal sulfates seen in ambient Atlanta aerosol are likely the product of both primary emission
sources as well as secondary reactions.
In the multi-energy maps, S0 always occurs with S+VI
(Fig. S3), suggesting they are either co-emitted as a primary
source or linked by a secondary formation process that occurs in the atmosphere. Up to 20 % of the sulfur in individual
particles was in the reduced form as S0 . Previous examinations of ambient aerosol have reported less than 5 % of total
sulfur as reduced sulfur (Cozzi et al., 2009; Long et al., 2014)
and have suggested incomplete combustion or incinerator
emissions as the likely source (Andersson et al., 2006; Bao et
al., 2009; Matsumoto et al., 2006). Common primary emission sources, such as gasoline and diesel exhaust, coal fly ash,
and biomass burning, did not contain S0 as a readily identifiable constituent in bulk S-NEXFS spectra, leaving the source
of reduced S in ambient Atlanta aerosol unresolved. While
emission sources were not analyzed at the individual particle level, bulk S-NEXFS of Azotobacter vinelandii revealed
this bacterium to be the only analyzed emission source to be
enriched in S0 . Microbial cells are increasingly recognized
as an important natural component of aerosol (Burrows et
al., 2009; Bauer et al., 2002). The ubiquitous distribution of
bacteria makes aerosolized soil bacteria, such as Azotobacter
vinelandii, another potential primary source of S0 . Furthermore, S0 was commonly found in individual particles, which
constitute the largest particle size fraction of these samples
(> 1 µm). This could further support the hypothesis that the
S0 is from aerosolized soil bacteria, which would reside in
larger particles.
The reduced sulfur found in ambient aerosol particles
could also be a result of secondary formation processes that
occur in the atmosphere. In a previous study, S+IV found in
ambient particle matter was attributed to the absorption and
incorporation of sulfur dioxide (S+IV ) into atmospheric particulate matter (Higashi and Takahashi, 2009). Theoretically,
a similar mechanism could help explain the finding of S0 in
ambient aerosols; however, gaseous phases of reduced sulfur compounds are unlikely to absorb onto an aerosol surface or condense without undergoing oxidation (Alexander
www.atmos-chem-phys.net/16/13389/2016/
13395
et al., 2005; Liao et al., 2003). Furthermore, reduced sulfur
species on the surface of a particle would be easily oxidized
by ozone, oxygen, or the hydroxyl radical, suggesting that
only reduced sulfur inside of a heterogeneous particle would
be likely to survive (Long et al., 2014), further suggesting
that the S0 likely has a primary source.
The composition and oxidation state of sulfur in ambient
aerosol provide insights for atmospheric chemistry involving
sulfur as well as metals. More than 25 % of the bulk sulfate
composition can be attributed to metal sulfates, which cannot be accounted for by our primary sources alone (Hu et al.,
2014). The solubilization of metals with sulfuric acid during atmospheric transport likely plays a role in forming the
metal sulfates observed in this study as well as others (Oakes
et al., 2012a). Reduced sulfur was also found to account for
up to 20 % of the total sulfur in individual particles, which is
a higher fraction than typically observed in ambient aerosol
samples (Long et al., 2014; Cozzi et al., 2009). As is the case
with previous studies that have noted reduced sulfur in ambient aerosol samples, the S0 is likely from a primary emission
source. Incomplete combustion is the most commonly cited
source of reduced sulfur compounds found in aerosol (Long
et al., 2014; Cozzi et al., 2009; Bao et al., 2009; Matsumoto
et al., 2006; Andersson et al., 2006); however, in this study,
a bacterium was the only potential primary emission source
to contain S0 at the bulk level. This suggests that aerosolized
bacteria may contribute to the S0 seen in ambient Atlanta
aerosol.
5
Data availability
The data used to produce these results is available upon request to the corresponding author. Data from sulfur standards
are available in the Supplement.
The Supplement related to this article is available online
at doi:10.5194/acp-16-13389-2016-supplement.
Acknowledgements. This material is based upon work supported
by the National Science Foundation under grants OCE-1357375
(EDI), as well as support from Southern Company (AGR). Any
opinions, findings, and conclusions or recommendations expressed
in this material are those of the authors and do not necessarily
reflect the views of the National Science Foundation.
Edited by: H. Su
Reviewed by: two anonymous referees
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